Bidirectional texture function

Bidirectional texture function (BTF) [1][2][3] is a 6-dimensional function depending on planar texture coordinates (x,y) as well as on view and illumination spherical angles. In practice this function is obtained as a set of several thousand color images of material sample taken during different camera and light positions.

The BTF is a representation of the appearance of texture as a function of viewing and illumination direction. It is an image-based representation, since the geometry of the surface is unknown and not measured. BTF is typically captured by imaging the surface at a sampling of the hemisphere of possible viewing and illumination directions. BTF measurements are collections of images. The term BTF was first introduced in [1][2] and similar terms have since been introduced including BSSRDF [4] and SBRDF (spatial BRDF). SBRDF has a very similar definition to BTF, i.e. BTF is also a spatially varying BRDF.

To cope with a massive BTF data with high redundancy, many compression methods were proposed.[3][5]

Application of the BTF is in photorealistic material rendering of objects in virtual reality systems and for visual scene analysis,[6] e.g., recognition of complex real-world materials using bidirectional feature histograms or 3D textons.

Biomedical and biometric applications of the BTF include recognition of skin texture.[7]

See also

References
  1. Kristin J. Dana; Bram van Ginneken; Shree K. Nayar; Jan J. Koenderink (1999). "Reflectance and texture of real world surfaces". ACM Transactions on Graphics, vol. 18, No. 1. pp. 1–34.
  2. Kristin J. Dana; Bram van Ginneken; Shree K. Nayar; Jan J. Koenderink (1996). "Reflectance and texture of real world surfaces". Columbia University Technical Report CUCS-048-96. Missing or empty |url= (help)
  3. Jiří Filip; Michal Haindl (2009). "Bidirectional Texture Function Modeling: A State of the Art Survey". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, No. 11. 31 (11): 1921–1940. doi:10.1109/TPAMI.2008.246. PMID 19762922.
  4. Jensen, H.W.; Marschner, S.R.; Levoy, M.; Hanrahan, P. (2001). "A practical model for subsurface light transport". ACM SIGGRAPH. pp. 511–518. Missing or empty |url= (help)
  5. Vlastimil Havran; Jiří Filip; Karol Myszkowski (2009). "Bidirectional Texture Function Compression based on Multi-Level Vector Quantization". Computer Graphics Forum, vol. 29, no. 1. pp. 175–190. Archived from the original on 2010-08-04.
  6. Michal Haindl; Jiří Filip (2013). Visual Texture: Accurate Material Appearance Measurement, Representation and Modeling. Advances in Computer Vision and Pattern Recognition, © Springer-Verlag London 2013. p. 285. ISBN 978-1-4471-4901-9.
  7. Oana G. Cula; Kristin J. Dana; Frank P. Murphy; Babar K. Rao (2005). "Skin Texture Modeling". International Journal of Computer Vision. pp. 97–119. Missing or empty |url= (help)
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